Evidence map›Paper›PMID 33436614›Full record

ReviewNature communications2021

Mechanisms of muscle atrophy and hypertrophy: implications in health and disease.

Roberta Sartori, Vanina Romanello, Marco Sandri

Abstract readReview
In one paragraph

Review in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 556 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
556citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

556 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Circulating biomarkers in older adults with and without sarcopenia: a systematic review and meta-analysis.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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496 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Roberta SartoriDepartment of Biomedical Sciences, University of Padova, via Ugo Bassi 58/b, 35121, Padova, Italy.
Vanina RomanelloDepartment of Biomedical Sciences, University of Padova, via Ugo Bassi 58/b, 35121, Padova, Italy. vanina.romanello@unipd.it.ORCID 0000-0002-7712-6416
Marco SandriDepartment of Biomedical Sciences, University of Padova, via Ugo Bassi 58/b, 35121, Padova, Italy. marco.sandri@unipd.it.ORCID 0000-0001-8509-7558

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle is the protein reservoir of our body and an important regulator of glucose and lipid homeostasis. Consequently, the growth or the loss of muscle mass can influence general metabolism, locomotion, eating and respiration. Therefore, it is not surprising that excessive muscle loss is a bad prognostic index of a variety of diseases ranging from cancer, organ failure, infections and unhealthy ageing. Muscle function is influenced by different quality systems that regulate the function of contractile proteins and organelles. These systems are controlled by transcriptional dependent programs that adapt muscle cells to environmental and nutritional clues. Mechanical, oxidative, nutritional and energy stresses, as well as growth factors or cytokines modulate signaling pathways that, ultimately, converge on protein and organelle turnover. Novel insights that control and orchestrate such complex network are continuously emerging and will be summarized in this review. Understanding the mechanisms that control muscle mass will provide therapeutic targets for the treatment of muscle loss in inherited and non-hereditary diseases and for the improvement of the quality of life during ageing.

Indexed as

DiseaseHealthAnimalsHumansHypertrophyMuscle DevelopmentMuscular AtrophySignal Transduction

Identifiers

PMID33436614
PMCPMC7803748

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.